Many persons, particularly when charged with management authority in commercial circumstances, are frequently faced with the need to make important decisions which must be based on the best information available. In such circumstances, it is considered to be a good practice to seek input from persons having recognized expertise with subject matter which is relevant to various aspects of the decision to be made. Therefore, it is desirable to not only locate persons with suitable expertise but also quantitatively evaluate not only their expertise but the level and quality of assistance they have been able to provide when their expertise has been previously sought by the decision-maker and others. Thus, when an informed decision is to be made, the decision-maker is required to actively pursue subject matter experts who may not be initially known to the decision-maker. At the present state of the art, messaging systems would be convenient for the numerous communications that would be involved in a search for suitable experts.
One technique for locating subject matter experts is by searching a directory that scans profiles of persons for whom records are kept, such as employees of a company, to locate persons who are likely to have developed expertise in regard to particular subject matter through their experience within the company or through prior experience or study. Such searching is somewhat difficult, however, because such profiles are not optimal indicators of a person's expertise and do not generally reflect the quality of assistance they have provided in the past or are likely to provide in the future. Thus, it is often at least equally effective, due to some level of existing social knowledge, to attempt to locate subject matter experts through associations (either personal associations or interest area organizations) and referrals from others with whom the decision-maker is acquainted. However, while social structures that may develop around a decision-maker may contain a large amount of collective experience, they often have little organizational structure that can be exploited in regard to particular subject matter expertise and therefore searching through such informal social structures can be quite time-consuming with no guarantee of success in locating a person with particular subject matter expertise or any assurance of the comparative quality of the expert that is found.
In social networking, relationships are usually built on trust developed over time between individuals. Currently, so-called recommender systems are known which attempt to leverage a metric of trust in order to recommend particular items of a set of items based on a function of trust between two individuals. However, such systems rely on manual input of information in regard to the metric of trust; which manual input may be inconsistently performed and difficult to maintain. Further, such systems are difficult to integrate with any system for facilitating the ultimate function of obtaining useful information.
Rating arrangements are also known which may provide for quantitative comparisons among experts. However, inputs to such arrangements are generally subject to subjective judgement and, therefore, inconsistency in quantitative ratings. Further, such arrangements are subject to being biased by collusion between persons being rated and those providing input to the rating arrangement and are otherwise difficult to control and administer. Moreover, like recommender systems, rating arrangements only develop through manual input.